CU-TMP: Temporal relation classification using syntactic and semantic features

Steven Bethard; James H. Martin

CU-TMP: Temporal relation classification using syntactic and semantic features

Research output: Contribution to conference › Paper › peer-review

Abstract

We approached the temporal relation identification tasks of TempEval 2007 as pair-wise classification tasks. We introduced a variety of syntactically and semantically motivated features, including temporal-logicbased features derived from running our Task B system on the Task A and C data. We trained support vector machine models and achieved the second highest accuracies on the tasks: 61% on Task A, 75% on Task B and 54% on Task C.

Original language	English (US)
Pages	129-132
Number of pages	4
State	Published - 2007
Externally published	Yes
Event	4th International Workshop on Semantic Evaluations, SemEval 2007 - Prague, Czech Republic Duration: Jun 23 2007 → Jun 24 2007

Other

Other	4th International Workshop on Semantic Evaluations, SemEval 2007
Country/Territory	Czech Republic
City	Prague
Period	6/23/07 → 6/24/07

ASJC Scopus subject areas

Computational Theory and Mathematics
Computer Science Applications
Theoretical Computer Science

Cite this

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title = "CU-TMP: Temporal relation classification using syntactic and semantic features",

abstract = "We approached the temporal relation identification tasks of TempEval 2007 as pair-wise classification tasks. We introduced a variety of syntactically and semantically motivated features, including temporal-logicbased features derived from running our Task B system on the Task A and C data. We trained support vector machine models and achieved the second highest accuracies on the tasks: 61% on Task A, 75% on Task B and 54% on Task C.",

author = "Steven Bethard and Martin, {James H.}",

note = "Funding Information: This research was performed under an appointment of the first author to the DHS Scholarship and Fellowship Program, administered by the ORISE through an interagency agreement between DOE and DHS. ORISE is managed by ORAU under DOE contract number DE-AC05-06OR23100. All opinions expressed in this paper are the author{\textquoteright}s and do not necessarily reflect the policies and views of DHS, DOE, or ORAU/ORISE. Publisher Copyright: {\textcopyright} 2007 Association for Computational Linguistics.; 4th International Workshop on Semantic Evaluations, SemEval 2007 ; Conference date: 23-06-2007 Through 24-06-2007",

year = "2007",

language = "English (US)",

pages = "129--132",

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T2 - 4th International Workshop on Semantic Evaluations, SemEval 2007

AU - Bethard, Steven

AU - Martin, James H.

N1 - Funding Information: This research was performed under an appointment of the first author to the DHS Scholarship and Fellowship Program, administered by the ORISE through an interagency agreement between DOE and DHS. ORISE is managed by ORAU under DOE contract number DE-AC05-06OR23100. All opinions expressed in this paper are the author’s and do not necessarily reflect the policies and views of DHS, DOE, or ORAU/ORISE. Publisher Copyright: © 2007 Association for Computational Linguistics.

PY - 2007

Y1 - 2007

N2 - We approached the temporal relation identification tasks of TempEval 2007 as pair-wise classification tasks. We introduced a variety of syntactically and semantically motivated features, including temporal-logicbased features derived from running our Task B system on the Task A and C data. We trained support vector machine models and achieved the second highest accuracies on the tasks: 61% on Task A, 75% on Task B and 54% on Task C.

AB - We approached the temporal relation identification tasks of TempEval 2007 as pair-wise classification tasks. We introduced a variety of syntactically and semantically motivated features, including temporal-logicbased features derived from running our Task B system on the Task A and C data. We trained support vector machine models and achieved the second highest accuracies on the tasks: 61% on Task A, 75% on Task B and 54% on Task C.

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Y2 - 23 June 2007 through 24 June 2007

ER -

CU-TMP: Temporal relation classification using syntactic and semantic features

Abstract

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ASJC Scopus subject areas

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